Adjustable Robust Optimization Algorithm for Residential Microgrid Multi-Dispatch Strategy with Consideration of Wind Power and Electric Vehicles

Shi, Ruifeng; Li, Shaopeng; Sun, Changhao; Lee, Kwang Y.

doi:10.3390/en11082050

Cited by 18 publications

(4 citation statements)

References 37 publications

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“…To preserve the stability of power grid operation, the traditional control mode in microgrids adopts droop control. However, although the traditional droop control can realize the primary grid regulation of voltage and active power, it overlooks the operation cost of distributed generation, resulting in resource waste [8]. Therefore, realizing the economic operation of microgrid while maintaining the stability of power grid is an important issue to be considered in microgrid operation control [9].…”

Section: Introductionmentioning

confidence: 99%

Distributed Economic Control for AC/DC Hybrid Microgrid

Wang

Yue

et al. 2021

Electronics

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In this paper, a new double-layer droop control mode for island AC/DC microgrids is proposed to realize autonomous and cost-effective operation. The optimal power reference iterative algorithm is used to realize the internal active power distribution in the subnet. On this basis, secondary frequency and voltage adjustments are introduced to realize the economic operation, autonomy and stability of the subnet. At the microgrid level, the local control strategy of cost micro increment deviation is designed to optimize the exchange power between subnets. The cooperation of the two can realize the global economic operation of the microgrid, as well as voltage following and frequency regulation in the subnet. Based on the hybrid AC/DC microgrid simulation model, the effectiveness of the proposed method is verified.

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Section: Introductionmentioning

confidence: 99%

Distributed Economic Control for AC/DC Hybrid Microgrid

Wang

Yue

et al. 2021

Electronics

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“…In Reference 34, simultaneous uncertainties are taken from wind power and electric vehicle charging loads, then provided a robust economic dispatch method for grid‐connected MGs, where a dispatch interval coefficient is suggested for handling the issue of over‐conservatism of strong optimization. Practical case studies prove the flexibility of this proposed dispatch approach.…”

Section: Introductionmentioning

confidence: 99%

S2NA‐GEO method–based charging strategy of electric vehicles to mitigate the volatility of renewable energy sources

Ilango¹,

Rajesh

Shajin

2021

Int Trans Electr Energ Syst

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In this manuscript, an efficient hybrid strategy is proposed to mitigate the negative impact of RES output fluctuations and smart charging method of electric vehicles (EVs). The proposed hybrid system is the joint implementation of Spike Neural Network Learning Algorithm (S2NA) algorithm and Golden Eagle Optimizer (GEO) algorithm; hence, it is known as S2NA-GEO strategy. An innovative uncertainty mode of renewable energy sources (RESs) based upon S2NA-GEO strategy is proposed, which can avert the difficult parameter collection and formula derivation. Price-based mode is accepted as EVs are considered responsive loads, which also take into account the spatial-temporal uncertainty of electric vehicles. Here, two fluctuation indexes are determined as quantitative evaluation of the volatility of RESs, then the charging cost is adopted as a guideline for the satisfaction of electric vehicle charging. The main purpose of the proposed system is diminishing

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“…V2G with OC and CE in [27] was elaborated without PTC. In [28], V2G with OC and PTC was expressed without CE cost function and PV generation. V2G with OC and PTC was taken in [28] and [29] while the additional cost factor of CE was also considered in [29].…”

mentioning

confidence: 99%

“…In [28], V2G with OC and PTC was expressed without CE cost function and PV generation. V2G with OC and PTC was taken in [28] and [29] while the additional cost factor of CE was also considered in [29]. Table 1 shows a summary of relevant research that was performed on EVs in recent times.…”

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confidence: 99%

Energy Cost Optimization of Hybrid Renewables Based V2G Microgrid Considering Multi Objective Function by Using Artificial Bee Colony Optimization

et al. 2020

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The worldwide demand for reduction of CO2 pollution, with more penetration of renewable energy sources and an increased number of electric vehicles (EVs), demonstrates the importance of economic dispatch (ED) with taking into account the reduction of CO2 emission. ED is a classical problem in which EVs impose more penetration as a dynamic load, and its impact as vehicle-to-grid (V2G) is the possible future trend with cost minimization. Based on the integration of EVs and hybrid renewable sources concerning both economic dispatch and pollution minimization, the multi-objective function is converted into a single comprehensive objective by using the judgment matrix methodology. In this paper, the investigation involves the minimization of the cost of all three objectives viz. operation cost, pollution cost, and carbon emissions with ED by incorporating V2G technology. The algorithms which include particle swarm optimization, as well as artificial bee colony, are applied under various operation and control strategies. The proposed models are verified and analyzed with different case studies. In terms of operation economics, the simulation results validate the superior performance of EVs based microgrid (MG) model in the coordinated charging and discharging mode. Further, the comparison of both algorithms shows better results with the ABC algorithm in terms of cost minimization of all objectives. ABC is better in V2G based microgrid with coordinated charging and discharging mode while its performance is significant during a large number of EVs (i.e., 700 EVs). Moreover, the load shedding scenarios are integrated which enables the MG system to operate in dual mode (i.e., seamless transition). In this paper, the main contribution involves penetration of EVs as dynamic load and its V2G impact in a coordinated or uncoordinated way, application of ABC algorithm for this particular load problem with improved results, and inclusion of short-term load shedding scenarios. INDEX TERMS Vehicle-to-grid (V2G), electrical vehicles (EVs), particle swarm optimization (PSO), artificial bee colony (ABC), dynamic ED, operating cost (OC), pollutant treatment cost (PTC), carbon dioxide emission (CE). NOMENCLATURE ABBREVIATIONS PG Power Grid WT Wind Turbine MT Micro Gas Turbine The associate editor coordinating the review of this manuscript and approving it for publication was Yanbo Chen .

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Adjustable Robust Optimization Algorithm for Residential Microgrid Multi-Dispatch Strategy with Consideration of Wind Power and Electric Vehicles

Cited by 18 publications

References 37 publications

Distributed Economic Control for AC/DC Hybrid Microgrid

Distributed Economic Control for AC/DC Hybrid Microgrid

S2NA‐GEO method–based charging strategy of electric vehicles to mitigate the volatility of renewable energy sources

Energy Cost Optimization of Hybrid Renewables Based V2G Microgrid Considering Multi Objective Function by Using Artificial Bee Colony Optimization

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